Haibin Lin

3.0k citations
18 papers · 1.2k indexed · 1 hit paper · h-index 8

Haibin Lin

13 papers receiving 1.2k citations

Hit Papers

ResNeSt: Split-Attention Networks6292022202620232024200400600

Peers

Haibin Lin
Comparison fields: 5 of 143
  • Computer Vision and Pattern Recognition 502
  • Artificial Intelligence 455
  • Media Technology 103
  • Computational Mathematics 5
  • Computer Networks and Communications 179
Replace Brian C. Van Essen with:
Brian C. Van Essen United States
Yuxing Peng China
Pengzhen Ren Australia
Mohd. Samar Ansari India
Zhonglong Zheng China
Yun Xiao China
Suk‐Hwan Lee South Korea
Vasileios Argyriou United Kingdom
Zhi Zhang China
Haibin Lin relative to Brian C. Van Essen United States Brian C. Van Essen's profile →
Citations per field
00.5×3.1×
Brian C. Van Essen · 1×
Citations per year

Countries citing papers authored by Haibin Lin

Since Specialization
Citations

This map shows the geographic impact of Haibin Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Haibin Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haibin Lin more than expected).

Fields of papers citing papers by Haibin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Haibin Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Haibin Lin. The network helps show where Haibin Lin may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Haibin Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Haibin Lin Line = papers co-authored together Haibin Lin links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 20250
2 20250
3 20250
4 20251
5 20248
6 202445
7 20240
8 20241
9 202314
10
ResNeSt: Split-Attention Networksbreakdown →
2022629
11
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
2020109
12
CSER: Communication-efficient SGD with Error Reset.
20206
13 202036
14
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
2019260
15
Self-Driving Database Management Systems.
2017130
16 20131
17 20130
18 20133

About Haibin Lin

Haibin Lin is a scholar working on Computational Mathematics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Topic Modeling (3 papers), Computer Graphics and Visualization Techniques (3 papers), Parallel Computing and Optimization Techniques (3 papers), Conducting polymers and applications (2 papers), Advanced Vision and Imaging (2 papers), Stochastic Gradient Optimization Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (502 citations), Artificial Intelligence (455 citations) and Media Technology (103 citations). Haibin Lin has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Alexander J. Smola, Mu Li, Tong He, Yi Zhu, Zhongyue Zhang, Hang Zhang, Jonas Mueller, Yue Sun, Zhi Zhang and R. Manmatha. Their work appears in journals such as Scientific Reports, Chemical Engineering Journal and Talanta.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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